Mohd Amri Md Yunus

Novel Planar Electromagnetic Sensors for Detection of Nitrates and Contamination in Natural Water Sources

This paper introduces novel sensors based on the combination of planar meander and interdigital electromagnetic sensors for monitoring the level of contamination in water sources. A series of experiments was conducted to determine the sensors characteristics. Two nitrates forms, namely sodium nitrates and ammonium nitrates, were mixed in several different ratios dissolved in 1 L of distilled water and were used to observe the response of the sensors. Initial results show that the sensors can detect very well the presence of nitrate added in distilled water. Furthermore, the contamination level of water samples which were taken from various sources and locations in New Zealand have been determined using the sensor, and the results was compared with the results obtained using nuclear magnetic resonance (NMR) technique. The outcomes show a very good correlation of contamination level with the output response of the sensor. The work and improvement for future consideration are discussed in this paper.

Planar Electromagnetic Sensor Based Estimation of Nitrate Contamination in Water Sources Using Independent Component Analysis

The main advantages of electromagnetic sensors can be listed as low-cost, convenient, suitable for in-situ measurement system, rapid response, and high durability. In this paper, the output parameters of the planar electromagnetic sensor have been observed with different kind of water samples at different concentrations. The output parameters have been derived and tested to be incorporated with independent component analysis (ICA) and used as inputs for an analysis model. The analysis model targeted to estimate the amount of nitrate contamination in water samples with the assistance of ICA based on FastICA fixed point algorithm under the contrast functions of pow3, tanh, gauss, and skew. Nitrates sample in the form of ammonium nitrates (NH4NO3), each of different concentration between 5 mg and 20 mg dissolved in 1 litre of deionized water (Milli-Q) was used as one of the main references. The analysis model was tested with eight sets of mixed NH4NO3 and (NH4)2HPO4 water samples. It is seen from the results that the model can acceptably detect the presence of nitrate added in Milli-Q water and capable of distinguishing the concentration level in the presence of other type of contamination. The system and approach presented in this paper has the potential to be used as a useful low-cost tool for water sources monitoring.

A WiFi based smart wireless sensor network for monitoring an agricultural environment

This paper reports the design and development of a smart wireless sensor network (WSN) for an agricultural environment. Monitoring agricultural environments for various factors such as temperature and humidity along with other factors can be of significance. The ability to document and detail changes in parameters of interest has become increasingly valuable. Investigations were performed for a remote monitoring system using WiFi, where the wireless sensor nodes are based on WSN802G modules. These nodes send data wirelessly to a central server, which collects the data, stores it and allows it to be analyzed and displayed as needed.

Nitrate and Sulfate Estimations in Water Sources Using a Planar Electromagnetic Sensor Array and Artificial Neural Network Method

The primary advantages of planar electromagnetic sensors can be listed as low cost, convenient, suitable for in situ measurement systems, rapid reaction, and highly durable. In this paper, the outputs of a planar electromagnetic sensors array were observed and analyzed after testing it with different types of water samples at different concentrations. The output parameters were derived to decompose by wavelet transform. The energy and mean features of decomposed signals were extracted and used as inputs for an artificial neural network (ANN) model. The analysis model was targeted to classify the amount of nitrate and sulfate contamination in water. Nitrates and sulfate samples in the form of KNO3 and K2SO4, each having different concentrations between 5 and 114 mg dissolved in 1 L of distilled water, were used. Furthermore, the analysis model was tested with seven sets of mixed KNO3 and K2SO4 water samples. A three-layer multilayer perceptron is used as a classifier. It is understood from the results that the model can detect the presence of nitrate and sulfate added in distilled water and is capable of distinguishing the concentration level in the presence of other types of contamination with a root mean square error (RMSE) of 0.0132. The validity of the ANN model was verified by removing the ANN model in estimating the water contamination, where the RMSE rose to 0.0977. The system and approach presented in this paper have the potential to be used as a useful low-cost tool for water source monitoring.

Concentration measurements of bubbles in a water column using an optical tomography system

Optical tomography provides a means for the determination of the spatial distribution of materials with different optical density in a volume by non-intrusive means. This paper presents results of concentration measurements of gas bubbles in a water column using an optical tomography system. A hydraulic flow rig is used to generate vertical air-water two-phase flows with controllable bubble flow rate. Two approaches are investigated. The first aims to obtain an average gas concentration at the measurement section, the second aims to obtain a gas distribution profile by using tomographic imaging. A hybrid back-projection algorithm is used to calculate concentration profiles from measured sensor values to provide a tomographic image of the measurement cross-section. The algorithm combines the characteristic of an optical sensor as a hard field sensor and the linear back projection algorithm.

A WiFi based smart wireless sensor network for an agricultural environment

The main objective of the present work is to develop a smart wireless sensor network (WSN) for an agricultural environment. Monitoring of environmental factors have increased in importance over the last decade. In particular monitoring agricultural environments for various factors such as temperature and humidity along with other factors can be of significance. A traditional approach to measuring these factors in an agricultural environment meant individuals manually taking measurements and checking them at various times. The ability to document and detail changes in parameters of interest have become increasingly valuable, to such an extent that unattended monitoring systems have been investigated for this function. This study investigates a remote monitoring system using WiFi, where the wireless sensor nodes are based on WSN802G modules. These nodes send data wirelessly to a central server, which collects the data, stores it and will allow it to be analyzed then displayed as needed.

Development of a low cost system for nitrate and contamination detections in natural water supply based on a planar electromagnetic sensor

The main objective of the present work is to develop a low-cost system for detection of nitrate and contamination in natural water resources based on a planar electromagnetic sensor. The functions and attributes of the low cost system based on planar meander and interdigital structure are discussed. The performance of the system was observed where the sensor was tested with two aqueous solutions of nitrates forms namely, sodium nitrates (NaNO3) and ammonium nitrates (NH4NO3), each of different concentration between 5 mg and 20 mg dissolved in 1 litre of mili-q water. Furthermore, it was also tested with various kinds of natural water samples taken from natural sources around New Zealand. The results from the first set of experiments show good linear correlations with the amount of concentration of nitrate forms in mili-q water. Favourably, the second experiments outcomes involving the water sample taken from various places around New Zealand also show a good correlation of contamination level as compared with results obtained from Nuclear Magnetic Resonance (NMR) measurement. The improvements for future consideration are also discussed.

Planar Electromagnetic Sensor for the Detection of Nitrate and Contamination in Natural Water Sources Using Electrochemical Impedance Spectroscopy Approach

This paper highlights the progress of developing a low-cost system for detection of nitrate and contamination in natural water resources based on a planar electromagnetic sensor which consists of meander and interdigital structure. The sensor has been operated and evaluated using electrochemical impedance spectroscopy (EIS) approach, based on estimated electrical model; the results obtained from the experiments were interpreted. The objectives of the present work are to conduct simulation, experiments and analysis of a new nitrate detection method using novel planar electromagnetic sensors by means of electrochemical spectroscopy analysis. The sensor was tested with two aqueous solutions of nitrates forms namely, sodium nitrates (NaNO3) and ammonium nitrates (NH4NO3), each of different concentration between 5 mg and 20 mg dissolved in 1 litre of distilled water to observe their response. Furthermore, the sensor was tested with various kinds of prepared samples and natural water samples taken from natural sources around New Zealand. The simulation results using COMSOL have assisted in understanding the characteristic and response of the sensor to the change of properties in the aqueous solution. The experimental results have authenticated the results obtained from the simulation and show the sensor can well detect the presence of nitrate added in distilled water and distinguish the concentration level from the calculated sensitivities. The experiment results with the water sample taken from various places around New Zealand show a very good correlation of contamination level, translated from the qualitative and quantitative results. The work and improvement for future consideration are also discussed in this chapter.

A new method for monitoring ammonium nitrate contamination in natural water sources based on independent component analysis

A system that measures impedance of a novel planar electromagnetic sensor successfully estimated the amount of ammonium and nitrate contaminations in natural water sources with the use of independent component analysis. The system employs a planar electromagnetic sensor which is simple to construct, reliable, and low cost. In this paper we have reported the achievement of extending the detecting capabilities of the sensor using independent component analysis to estimate ammonium nitrate contamination in water sources supply with good accuracy. The outcomes show a very good estimation of contamination level with the output response of the sensor and independent component analysis method.

A review on the design and development of turbidimeter

Purpose – This paper aims to present a review of the design and development of the turbidimeter for measuring the turbidity level in water. Monitoring the turbidity level of water is important because it is related to public health. Design/methodology/approach – A precise and reliable turbidimeter can provide vital data that reveals the water condition level. Several turbidimeter units are discussed briefly. Three types of turbidimeter design – single beam, ratio and modulated four beams – are elaborated with some illustrations of the design concept. Various improvements and innovations for upgrading turbidimeter design are also discussed. Findings – This paper elaborated on a new method of estimating the water turbidity level in water samples using an optical tomography system based on the independent component analysis method. The results showed that a tomography-based turbidimeter can measure slight changes in the level of turbidity when the volume of contaminants is changed slightly. The turbidimeter ...